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Track: #DDVUG DWH Automation Challenge
- Mittwoch
21.06.
DWH automation is wonderful, but which tool? Using 13 typical data constellations, a fictitious data model is presented that can be used to evaluate the implementation performance of an automation tool. In 4 follow-up presentations, one implementation each will be presented based on the data.
Prerequisites: Basic Data Warehouse Knowledge
Level: Basic
Extended Abstract:
The automation of data warehouse development, especially in connection with Data Vault, drastically increases the speed of development in BI. Before using this technology, the question of the right tool for DWH automation arises:
- Does the tool fulfil all the necessary functionalities?
- What are the necessary functionalities in the first place?
- What suits the existing team and the company technology or culture?
Based on several tool evaluations and with a lot of know-how about typical Data Vault problems, the German Data Vault User Group (DDVUG) has created a fictitious company: Willibald - seeds and plants.
A data model with 13 typical problems is available for this purpose. Based on these typical problems, the implementations within the DWH automation tools can be evaluated.
In this presentation, these challenges are described and a catalogue of criteria for selection and evaluation is presented. In four further presentations, users/manufacturers will show how the challenge was implemented, giving an impression of how to use the tool and an insight into general functions.
This is an ideal start to your own tool selection as well as an ideal opportunity to get a tool overview or to update your own tool overview.
Christian Hädrich is a BI specialist and has been supporting companies in the development of dispositive applications and data warehouses for over 20 years. Due to his mainframe background, he is often active at large companies such as insurance companies and banks. In addition to implementation, his work focuses on architecture and process consulting. For 8 years, he has been intensively involved with the topics of DWH automation and Data Vault. He is a member of the board of the German-speaking Data Vault User Group (DDVUG) e.V.
Michael Müller has been working in the BI field for 20 years. His focus is on data modeling and data architecture as well as on Data Vault, DWH automation and embedding BI into the company. He is currently on the board of the German-speaking Data Vault User Group (DDVUG) e.V.
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With the data of the fictitious company Willibald and its 13 challenges, a DWH is created with datavaultbuilder. An ideal opportunity to see and evaluate the tool in realistic use. The data of the company Willibald has been explained by DDVUG in session 1 previous lecture.
Prerequisites: Basic Data Warehouse Knowledge
Level: Basic
Extended Abstract:
The fictitious company Willibald has asked Datavault Builder to perform a POC for their new DWH. For this purpose, it has defined 13 typical challenges to be solved. In this talk we will present how the task was solved in Datavault Builder. For this, we agilely create a business model, which is automatically converted into working code. We load and analyse data, present the created documentation and data lineage and give an outlook on how the solution can be rolled out and operated.
About Datavault Builder
Datavault Builder is the award-winning business-driven data warehouse automation solution that allows you to trust your data and trust your decisions.
It is an efficient visual data integration solution replacing up to nine different software tools. Datavault Builder leverages standardization and cooperation between business and IT people as the key to success.
Increase productivity and benefit from the fastest possible time-to-insights without compromising on full auditability.
Petr Beles verfügt über fundierte Erfahrungen in Data-Warehouse-Projekten in den Bereichen Telekommunikation, Finanzen und Industrie. Seit mehreren Jahren führt er als Senior Consultant erfolgreich Projekte mit Data Vault durch. Nachdem er den Bedarf an Automatisierung mit Data Vault erkannt hatte, begann er zusammen mit seinen Kollegen mit der Entwicklung eines Automatisierungstools, das in der Erstellung des Datavault Builders gipfelte. Petr Beles ist heute CEO der 2150 Datavault Builder AG.
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Petr Beles (Data-Vault-Specialist, Senior Consultant) has profound experience in data warehouse projects in the telecommunications, financial and industrial sectors. For several years he has been successfully implementing projects with Data Vault and trains teams in the application of this data modelling technique.
With the data of the fictitious company Willibald and its 13 challenges, a DWH is created with the open source software dbt. An ideal opportunity to see and evaluate the tool in realistic use. The data of the company Willibald will be explained by DDVUG in a previous lecture.
Prerequisites: Basic Data Warehouse Knowledge
Level: Basic
Extended Abstract:
For the fictitious company Willibald, a complete data model with data is available that was created by DDVUG and provided with 13 typical challenges. In this presentation, a possible solution using dbt, datavault4dbt and our own extensions will be shown and combined into a complete data warehouse. This will give you an overall impression and the possibility to get your own comprehensive impression of the tool.
Dbt (data build tool) is a development framework that enables teams to build, test and deploy analytics solutions faster. It can be used to create a unified development environment for all data engineering and data analyst teams. Scalefree's open-source Datavault4dbt package extends dbt with dbt macros to build a Data Vault 2.0 compliant data warehouse.
In some places, we have supplemented this setup with self-developed macros. We have chosen Snowflake as the target platform, but other databases would also be possible for this setup, in part with a certain amount of adaptation.
In our view, the use of a data governance tool is highly recommended for the development of a data warehouse that can be maintained in the long term.
For this reason, we have extended our approach with an adapter to a graphical data governance tool to enable an almost completely automatic construction of the raw vault based on the centrally maintained metadata.
Andreas Haas has been working as a consultant in the business intelligence sector for over 20 years. During this time, he has successfully implemented data warehouse projects in various industries, mainly in the roles of data warehouse architect, data engineer and in project management. As a certified Data Vault 2.0 Practitioner, large metadata-driven Data Vault implementations are the main focus of his work.
Jan Binge has gained over 25 years of experience in the field of IT, out of which he has spent more than a decade as a freelance consultant specializing in "data warehouse design". Following his certification as a Datavault Practitioner in 2014, he has directed his attention towards modeling and developing data warehouse systems while also emphasizing the automation of creation processes.
With the data of the fictitious company Willibald and its 13 challenges, a DWH is created with VaultSpeed. An ideal opportunity to see and evaluate the tool in realistic use. The data of the company Willibald will be explained by DDVUG in a previous lecture.
Prerequisites: Basic Data Warehouse Knowledge
Level: Basic
Extended Abstract:
For the fictitious company Willibald, a complete data model with data is available that was created by DDVUG and provided with 13 typical challenges. In this presentation, the typical solutions are shown in VaultSpeed and combined to form a complete data warehouse. This will give you an overall impression and the opportunity to get your own comprehensive impression of the tool.
VaultSpeed provides a best-in-class data automation solution, building on the Data Vault 2.0 methodology. Enterprise customers worldwide rely on VaultSpeed to automate multi-source data integration as well as industry-specific metrics stores, on top of the integrated datasets. VaultSpeed is the default SaaS solution for companies looking to simplify the creation and maintenance of their data cloud.
VaultSpeed is headquartered in Leuven, Belgium, with offices in Seattle, USA and Vilnius, Lithuania. For more information, visit www.vaultspeed.com
Jonas De Keuster is VP Product Marketing at VaultSpeed. He had close to 10 years of experience as a DWH consultant in various industries like banking, insurance, healthcare, and HR services, before joining the company. This background allows him to help understand current customer needs and engage in conversations with members of the data industry.
With the data of the fictitious company Willibald and its 13 challenges, a DWH is created with WhereScape Data Vault Express. An ideal opportunity to see and evaluate the tool in realistic use. The data of the company Willibald will be explained by DDVUG in a previous lecture.
Prerequisites: Basic Data Warehouse Knowledge
Level: Basic
Extended Abstract:
For the fictitious company Willibald, a complete data model with data is available that was created by DDVUG and provided with 13 typical challenges. In this presentation, the typical solutions are shown in WhereScape and
combined to form a complete data warehouse. This will give you an overall impression and the opportunity to get your own comprehensive impression of the tool.
WhereScape Data Warehouse Automation software solves one of IT’s biggest problems: how do I build a Data Warehouse with efficiency, reduced risk, and long-term viability?
Using automation, templates, and built-in intelligence, WhereScape increases architect and developer productivity, provides scalability with standards and allows you to take control of your own data whilst fostering collaboration between IT and the business.
With its breadth of technical support, including virtually every source, target, and design methodology, WhereScape helps you design, develop, deploy, and operate your Data Vault (or any other data architecture) at speed with ease.
Create raw vaults, business vaults, and star schema in just a few minutes and realise the performance and quality improvements by reducing hand-offs, tool changes, and other pitfalls of hand-written or partially-automated development efforts.
Dr. Sultan Shiffa is a senior solutions architect at WhereScape, helping customers and partners to maximise their use of WhereScape across a broad range of target database platforms, modelling styles and design patterns. Previously he worked within Enterprise Data Management at IDERA, as an expert for complex and diverse data management solutions and methodologies. The two decades before that he worked as an Oracle Certified Professional (OCP) DBA and database consultant.
As the Operations Director at WhereScape, Simon Spring is dedicated to developing the product roadmap and meeting the demands of customers and partners in the constantly evolving data warehousing and analytics landscape. Trained in software engineering and with a wealth of experience in successful analytics projects spanning multiple technologies and industries, Simon combines his passion for technology and automation with his commercial background in software sales and professional services, bringing a distinctive outlook to the realm of Data Warehouse Automation.
Thomas Heuer, based in Germany, is an experienced business and communications professional in the field of IT / Business Intelligence. His background in channel & direct sales at Sony and Samsung gives him a distinct perspective on the IT industry. Thomas is a strong proponent of automation and helps his clients unlock the full potential of their data. As Sales Director EMEA he has a thorough knowledge of the benefits that data warehouse automation can bring to businesses of any scale, and he is dedicated to assisting his clients in achieving their objectives and advancing their organizations.
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Being well informed about tools and their capabilities is one thing, but what can I expect when I embark on data warehouse automation?
We have three experts with very different experiences and three completely different approaches who will talk about implementation, reasoning, development speed, costs/benefits, metadata and lessons learned in this panel discussion.
Andreas Buckenhofer arbeitet bei Mercedes-Benz Tech Innovation in Ulm als Lead Expert 'Vehicle Data Platforms'. Er verfügt über langjährige Erfahrung in der Entwicklung datenintensiver Produkte. Seine Schwerpunkte dabei sind insbesondere Datenarchitektur, Datenspeicherung, Datenintegration und Datenqualität.
Michael Kwiatkowski - Head of Data & AI at Volkswagen Commercial Vehicles. Together with his Team they had been early adaptors of Data Vault Automation Solutions within the Volkswagen Group.
Together with his Team they had been early adaptors of Data Vault Automation Solutions within the Volkswagen Group.
Oliver Grohmann - IT Staff Data Engineer at ams OSRAM - IT Data Analytics
As an IT Staff Data Engineer at ams OSRAM Oliver Grohmann is responsible for the Enterprise Data Model in the Cloud Data Warehouse. In the IT Data Analytics team he supports the setup and evolution of the Cloud Data Platform as well as the definition of implementation standards and best practices.
Christian Hädrich is a BI specialist and has been supporting companies in the development of dispositive applications and data warehouses for over 20 years. Due to his mainframe background, he is often active at large companies such as insurance companies and banks. In addition to implementation, his work focuses on architecture and process consulting. For 8 years, he has been intensively involved with the topics of DWH automation and Data Vault. He is a member of the board of the German-speaking Data Vault User Group (DDVUG) e.V.
Michael Müller has been working in the BI field for 20 years. His focus is on data modeling and data architecture as well as on Data Vault, DWH automation and embedding BI into the company. He is currently on the board of the German-speaking Data Vault User Group (DDVUG) e.V.
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The results of the DWH Automation Challenge are made available in a web-portal. The data and the data model for Willibald are made freely available.
A good reason to celebrate!
A pleasant way to end a long day on DWH automation and an exchange of ideas in a relaxed atmosphere.
Prerequisites: Basic Data Warehouse Knowledge
Level: Basic
Christian Hädrich is a BI specialist and has been supporting companies in the development of dispositive applications and data warehouses for over 20 years. Due to his mainframe background, he is often active at large companies such as insurance companies and banks. In addition to implementation, his work focuses on architecture and process consulting. For 8 years, he has been intensively involved with the topics of DWH automation and Data Vault. He is a member of the board of the German-speaking Data Vault User Group (DDVUG) e.V.
Michael Müller has been working in the BI field for 20 years. His focus is on data modeling and data architecture as well as on Data Vault, DWH automation and embedding BI into the company. He is currently on the board of the German-speaking Data Vault User Group (DDVUG) e.V.
Vortrag Teilen